This Research Topic is the fourth volume of the Research Topic "The State-of-Art Techniques of Seismic Imaging for the Deep and Ultra-deep Hydrocarbon Reservoirs". Please see the first volume here, the second volume here and the third volume here.
Deep and ultra-deep hydrocarbon reservoirs have become increasingly prominent targets in global oil and gas exploration following rapid technological and industrial advances over the past three decades. Unlike shallow to medium-depth reservoirs, these deeply buried systems possess distinctive hydrocarbon sources, accumulation mechanisms, and sweet-spot distribution patterns that require advanced imaging and interpretative approaches. Seismic imaging provides a powerful means to map subsurface structures and infer rock and fluid properties in three dimensions, playing a crucial role in identifying favorable reservoir zones. Numerous discoveries worldwide, including those in the Middle East, Gulf of Mexico, North Sea, and western China, attest to its effectiveness. However, as exploration moves into deeper and more complex settings, challenges such as low signal-to-noise ratios, difficulty in accurate velocity modeling, and reduced imaging resolution remain significant barriers to reliable subsurface characterization. In parallel, rapid progress in data mining, artificial intelligence (AI), and machine learning (ML) is reshaping how massive seismic datasets are processed, interpreted, and integrated with geological knowledge, opening new pathways to address these long-standing challenges.
This Research Topic aims to promote cutting-edge research and technological progress in seismic methods for deep and ultra-deep oil and gas exploration. The goal is to address the key scientific and technical challenges of imaging and interpreting deep reservoirs to enhance understanding of their petroleum systems and improve resource evaluation. Contributions are encouraged that present novel seismic preprocessing techniques to enhance signal clarity, robust velocity building approaches using tomography or full-waveform inversion, and advanced migration and imaging methodologies. We also welcome studies that leverage AI/ML and data-driven approaches, such as deep learning for denoising and signal enhancement, neural-network-assisted velocity model building, physics-informed neural networks for wave-equation inversion, automated fault and horizon interpretation, and intelligent reservoir characterization. The Topic further encourages studies that couple seismic attributes with geological interpretation, with or without ML assistance, to improve insights into hydrocarbon sources, accumulation processes, and preservation mechanisms in complex deep petroleum systems. By doing so, the Research Topic seeks to advance both theoretical understanding and practical applications supporting sustainable and efficient hydrocarbon development.
The scope of this Research Topic spans studies integrating theoretical developments, methodological advances, and case-based applications in seismic imaging and deep reservoir analysis. It welcomes diverse article types, including Original Research, Methods, Review, Technology and Code, and Perspective papers.
To gather further insights into seismic characterization of deep and ultra-deep reservoirs, we welcome articles addressing, but not limited to, the following themes: • Advanced seismic preprocessing techniques for enhancing the signal-to-noise ratio • Robust velocity building using travel-time tomography and full-waveform inversion • Seismic diffraction separation and imaging for complex geological conditions • Advanced ray-based and wave-equation-based migration techniques • Practical least-squares migration applications for deep imaging • Seismic imaging in attenuation and anisotropic media • AI and machine learning approaches for seismic data processing, imaging, and interpretation in deep reservoir settings • Physics-informed and data-driven inversion methods for velocity modeling and reservoir characterization • Novel insights into hydrocarbon source, accumulation, and preservation mechanisms in deep petroleum systems
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Data Report
Editorial
FAIR² Data
Hypothesis and Theory
Methods
Mini Review
Opinion
Original Research
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
